JP7114386B2 - Medical diagnostic imaging equipment and modality control equipment - Google Patents

Description

TECHNICAL FIELD Embodiments of the present invention relate to a medical image diagnostic apparatus, a modality control apparatus, and a medical information management apparatus.

In medical image diagnosis, the following problems are known when capturing images at the moment an attack related to a specific disease occurs. For example, when capturing an image by inducing a seizure, it is necessary to apply a load to the human body. Also, if the seizure cannot be induced, it is difficult to determine the timing of imaging because it is not known when the seizure will occur.

As an example, the assessment of angina pectoris requires coronary angiography studies to be performed in the presence of an attack. For example, exertional angina pectoris is diagnosed and evaluated by inducing an attack with an exercise load and photographing the moment the attack occurs. However, elderly people and patients with comorbidities may not be able to exercise. Therefore, it may not be possible to provoke a seizure during testing, and diagnostic evaluation may not be possible.

For example, coronary spastic angina is angina pectoris caused by spasm of the coronary arteries, and an exercise load cannot induce an attack. Although it is possible to induce seizures by the coronary spasm drug provocation test, it is not always possible for all people to undergo the test because it imposes a burden on the human body.

In other words, there is a problem that it is difficult to intentionally induce an attack caused by a specific disease such as angina pectoris when examining the specific disease. Therefore, conventionally, it has been difficult to perform a test on a subject suffering from the specific disease at the optimum timing.

Japanese translation of PCT publication No. 2016-514508

The problem to be solved by the present invention is to enable the inspection of the subject to be performed at the optimum timing.

A medical image diagnostic apparatus according to an embodiment includes an acquisition unit, a prediction unit, and a control unit. The acquisition unit acquires biological data of a subject in real time. The prediction unit predicts an occurrence time zone of an event related to the subject based on the biometric data and the probability distribution related to the event. The control unit controls imaging of the subject based on the occurrence time period.

1 is a block diagram showing a configuration example of a medical information processing system according to a first embodiment; FIG. FIG. 2 is a block diagram showing a configuration example of the medical image diagnostic apparatus in FIG. 1; 3 is a flowchart illustrating an operation in the first embodiment; FIG. FIG. 4 is a schematic diagram for explaining the operation in the first embodiment; FIG. 5 is a block diagram showing a configuration example of a medical information processing system according to a second embodiment; 6 is a block diagram showing a configuration example of the modality control device of FIG. 5; FIG. FIG. 7 is a flowchart illustrating operations in the second embodiment; FIG. 8 is a block diagram illustrating a network configuration including a medical information processing system according to a third embodiment; 9 is a block diagram showing a configuration example of the medical information management apparatus of FIG. 8; FIG. FIG. 10 is a flowchart illustrating operations in the third embodiment;

Hereinafter, embodiments of a medical image diagnostic apparatus, a modality control apparatus, and a medical information management apparatus will be described in detail with reference to the drawings.

(First embodiment)
FIG. 1 is a block diagram showing a configuration example of a medical information processing system according to the first embodiment. For example, as shown in FIG. 1, a medical information processing system 100 according to this embodiment includes a medical image diagnostic apparatus 110, a server apparatus 120, a terminal apparatus 130, and a biological data measuring apparatus 140. The medical image diagnostic apparatus 110, the server apparatus 120, the terminal apparatus 130, and the biological data measuring apparatus 140 are connected to each other via, for example, an in-hospital LAN (Local Area Network) 150 installed in the medical facility. The medical information processing system 100 may include multiple server devices and multiple terminal devices.

The medical information processing system 100 includes, for example, PACS (Picture Archiving and Communication System), HIS (Hospital Information System), and RIS (Radiology Information System). These systems are operated by, for example, an examination reservation system. The medical information processing system 100 comprehensively manages various types of information such as medical images, examination orders, and patient information.

FIG. 2 is a block diagram showing a configuration example of the medical image diagnostic apparatus shown in FIG. For example, as shown in FIG. 2, a medical image diagnostic apparatus 110 according to this embodiment includes a medical imaging apparatus 111, a memory 112, a display 113, an input interface 114, a processing circuit 115, and a communication interface. .

The medical image diagnostic apparatus 110 is an apparatus that performs an examination by photographing a subject. The medical image diagnostic apparatus 110 corresponds to, for example, an X-ray diagnostic apparatus, an X-ray computed tomography (CT) apparatus, a magnetic resonance imaging (MRI) apparatus, and the like. In one example, medical imaging apparatus 111 corresponds to a cradle, and memory 112, display 113, input interface 114, processing circuitry 115, and communication interface 116 correspond to a console connected to the cradle. X-ray diagnostic equipment, X-ray CT equipment, MRI equipment, etc. may be called modality equipment.

A medical imaging device 111 generates a medical signal relating to a subject. A medical signal is raw data collected by subjecting a subject to medical imaging. Therefore, the medical signal may be referred to as medical signal data. The medical signal data corresponds to, for example, projection data or sinogram data when the medical imaging apparatus 111 is an X-ray CT apparatus, or k-space data when it is an MRI apparatus.

When the medical imaging apparatus 111 is a frame of an X-ray diagnostic apparatus, the frame irradiates an object placed between the X-ray tube and the X-ray detector with X-rays. X-rays transmitted through the subject are detected by an X-ray detector. An X-ray detector generates an electrical signal having a crest value corresponding to the dose of detected X-rays. The electrical signal is converted into digital data via an A/D converter. The digital data is transmitted to processing circuitry 115 as raw data.

When the medical imaging apparatus 111 is a gantry for an X-ray CT apparatus, the gantry irradiates the subject with X-rays from the X-ray tube while rotating the X-ray tube and the X-ray detector around the subject. X-rays transmitted through the specimen are detected by an X-ray detector. An X-ray detector generates an electrical signal having a crest value corresponding to the dose of detected X-rays. The electrical signal is subjected to signal processing such as A/D conversion by a data acquisition circuit. The electric signal after A/D conversion is called projection data or sinogram data. The projection data or sinogram data are transmitted to processing circuitry 115 as raw data.

When the medical imaging apparatus 111 is the pedestal of the MRI apparatus, the pedestal is subjected to application of a static magnetic field via a static magnetic field magnet, application of a gradient magnetic field via a gradient magnetic field coil, and application of an RF pulse via a transmission coil. and repeat. A magnetic resonance (MR) signal is emitted from the subject due to the application of the RF pulse. Emitted MR signals are received via a receive coil. The received MR signal is subjected to signal processing such as A/D conversion by the receiving circuit. The MR signal after A/D conversion corresponds to k-space data. The k-space data is transmitted to processing circuitry 115 as raw data.

In other words, the medical imaging apparatus 111 subjects the subject to medical imaging according to the imaging principle according to the modality device type of the medical imaging apparatus 111, and collects raw data about the subject. The raw data collected is transmitted to processing circuitry 115 .

Note that the medical imaging apparatus 111 may generate medical image data by performing image restoration processing on the collected medical signal data. Medical image data corresponds to, for example, X-ray images, CT images, MR images, and the like.

Memory 112 stores various information. As the memory 112, for example, an HDD (Hard Disk Drive), an SSD (Solid State Drive), an integrated circuit storage device, or the like can be used as appropriate. Also, the memory 112 may be a drive device or the like that reads and writes various information from/to a portable storage medium such as a CD-ROM drive, a DVD drive, and a flash memory. For example, the memory 112 stores raw data and medical image data acquired by the medical imaging device 111 . The memory 112 also stores control programs and data according to the present embodiment. Note that the storage area of the memory 112 may be in an external storage device connected to the hospital LAN 150 .

The display 113 displays various information for the operator to perform various tasks. The display 113 displays, for example, a screen for inputting imaging conditions according to the type of the parity device, medical image data, and the like. Display 113 may suitably be, for example, a CRT display, liquid crystal display, organic EL display, LED display, plasma display, and any other display known in the art.

The input interface 114 is realized by, for example, a mouse, a keyboard, and a touch panel through which an instruction is input by touching an operation surface. The input interface 114 receives operations from an operator, for example. The operator's operation corresponds to, for example, a mouse pointer movement operation, a click operation, a drag-and-drop operation, and the like. The input interface 114 converts an operator's operation into an electrical signal and outputs the electrical signal to the processing circuit 115 . In this embodiment, the input interface 114 accepts imaging conditions and the like according to the modality device type from the operator.

The processing circuit 115 has, as hardware resources, a processor (not shown), ROM (Read-Only Memory), RAM and other memories, and controls the medical image diagnostic apparatus 110 . The processing circuit 115 has a system control function 115a, an image generation function 115b, an acquisition function 115c, a prediction function 115d and an imaging control function 115e. Various functions performed by the system control function 115a, the image generation function 115b, the acquisition function 115c, the prediction function 115d, and the imaging control function 115e are stored in the memory in the form of computer-executable programs. The processing circuit 115 is a processor that reads programs corresponding to these various functions from the memory and executes them to implement functions corresponding to each program. In other words, the processing circuit 115 in a state where each program has been read has a plurality of functions shown in the processing circuit 115 of FIG.

In FIG. 2, it is assumed that the single processing circuit 115 implements the various functions described above, but a plurality of independent processors may execute programs to implement the various functions. In other words, the various functions described above may be configured as programs, and one processing circuit may execute each program, or a specific function may be implemented in a dedicated, independent program execution circuit. good too.

The aforementioned term "processor" includes, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an Application Specific Integrated Circuit (ASIC) and a programmable logic device (e.g., a simple programmable logic device ( Simple Programmable Logic Device (SPLD), Complex Programmable Logic Device (CPLD) and Field Programmable Gate Array (FPGA)).

The processor in the processing circuit 115 implements various functions by reading and executing programs stored in the memory 112 . Note that instead of storing the program in the memory 112, the program may be configured to be directly embedded in the circuit of the processor. In this case, the processor implements its functions by reading and executing the program embedded in the circuit. The system control function 115a, the image generation function 115b, the acquisition function 115c, the prediction function 115d, and the imaging control function 115e of the processing circuit 115 are examples of the system control unit, the image generation unit, the acquisition unit, the prediction unit, and the control unit, respectively. is.

The system control function 115a is a function that controls each function of the processing circuit 115 based on an input operation received from an operator via the input interface 114. FIG. Specifically, the processing circuit 115 reads the control program stored in the memory 112 by the system control function 115a. The read control program is expanded on the memory in the processing circuit 115, and each part of the medical image diagnostic apparatus 110 is controlled according to the control program.

The image generation function 115b is a function for generating medical image data by performing processing according to the modality device type on the raw data output from the medical imaging device 111 . For example, when the medical imaging apparatus 111 is an X-ray diagnostic apparatus, the processing circuit 115 generates an X-ray image by performing various processes on raw data using the image generation function 115b. For example, when the medical imaging apparatus 111 is an X-ray CT apparatus, the processing circuit 115 generates a CT image by using the image generation function 115b to apply Filtered Back Projection (FBP) to the raw data. do. Also, if the medical imaging apparatus 111 is an MRI apparatus, the processing circuitry 115 generates MR images by using a Fast Fourier Transform (FFT) on the raw data.

The acquisition function 115c is a function for acquiring biological data of a subject in real time. For example, when the biometric data is an electrocardiographic waveform, the processing circuit 115 acquires the electrocardiographic waveform of the subject in real time by the acquisition function 115c. In addition, the processing circuit 115 may acquire biological data of the subject placed on the medical imaging apparatus 111 in real time. In addition, the processing circuit 115 acquires, in real time, biological data based on a medical image captured by a medical imaging apparatus (another medical imaging apparatus) of another medical image diagnostic apparatus connected via an in-hospital LAN, for example. good too. In addition, the processing circuit 115 may acquire biological data in real time based on a medical image captured by an ultrasonic diagnostic apparatus connected via an in-hospital LAN, for example.

The prediction function 115d is a function for predicting the occurrence time zone of an event related to the subject. Specifically, the prediction function 115d of the processing circuit 115 predicts the occurrence time zone of the event related to the subject based on the biological data of the subject acquired in real time and the probability distribution regarding the event. More specifically, processing circuitry 115 may predict the time of occurrence by updating probability distributions using biometric data. Further, the processing circuit 115 may calculate a probability distribution based on the subject's biological data and other biological data acquired in real time, and predict the occurrence time period. Other biometric data corresponds to group big data, for example, and is biometric data obtained from a plurality of subjects or a plurality of patients. Note that analysis methods such as simple regression analysis, multiple regression analysis, correlation analysis, and time series analysis (ARIMA model and SARIMA model) are used to calculate the probability distribution (or analyze biological data).

An event in this embodiment is, for example, a seizure that occurs irregularly (or suddenly). Irregularly occurring attacks include, for example, arrhythmias and coronary spastic angina. The probability distribution in this embodiment indicates the probability of occurrence of an event, for example, by the relationship between time and probability density. The occurrence time zone in this embodiment indicates a time zone in which an event may occur. Therefore, the time zone of occurrence corresponds to a period in which the probability density exceeds a certain threshold, for example. Note that the time period of occurrence may include the concept of time of occurrence.

For a specific event, the processing circuit 115 may use the prediction function 115d to calculate a probability distribution for each region in which the event will occur or predict the occurrence time period. For example, coronary spastic angina pectoris involves spasm in either the right or left coronary artery. Therefore, the processing circuit 115 may calculate probability distributions or predict the time period of spasm occurrence in each of the right and left coronary arteries.

In this embodiment, events and biometric data are assumed to have some correlation. For example, the processing circuitry 115 analyzes the biometric data to calculate a probability distribution based on the relationship that an event occurs after a pattern in the biometric data. Note that the predicted time of occurrence varies, and may be several minutes from now or several days from now.

For example, the following three methods are conceivable as methods for predicting the occurrence time zone of an event. The first is a method of predicting the occurrence time zone based on the real-time biometric data of the subject and the probability distribution based on the past biometric data of the subject. The second is a method of predicting an occurrence time zone based on the real-time biometric data of the subject and the probability distribution based on the past biometric data of other subjects regarding the event. The third is a method of predicting the occurrence time zone based on the real-time biometric data of the subject and the probability distribution based on the past biometric data of the subject and other subjects. Note that the PHR (Personal Health Record) of the subject or the PHR of another subject may be further used in predicting the occurrence time zone.

The imaging control function 115e is a function for controlling imaging of the subject based on the occurrence time period. Specifically, the processing circuit 115 uses the imaging control function 115e to control the start or end of imaging in the medical imaging apparatus 111 based on the occurrence time period. For example, if the medical imaging apparatus 111 is an apparatus capable of continuous imaging such as an X-ray CT apparatus and an MRI apparatus, the processing circuit 115 starts imaging when the probability of occurrence exceeds the threshold and You may finish imaging with . The processing circuitry 115 may also control the start or end of administration of the contrast agent to the subject based on the time period of occurrence.

The communication interface 116 performs data communication with the server device 120 , the terminal device 130 and the biological data measuring device 140 connected via the hospital LAN 150 . Any standard may be used for communication with the server device 120, the terminal device 130, and the biological data measuring device 140, and examples thereof include HL7, DICOM, or both.

The server device 120 corresponds to, for example, a PACS server. The server device 120 stores medical image data collected by the medical image diagnostic device 110 . Specifically, the server device 120 receives, for example, a plurality of examination orders from the terminal device 130 arranged in each clinical department. The server device 120 creates a patient list for each medical image diagnostic device 110 from the plurality of received examination orders. The server device 120 transmits the created patient list to the medical image diagnostic device 110 . The server device 120 also transmits medical image data to the terminal device 130 in response to a request from the terminal device 130 .

The terminal device 130 corresponds to, for example, a PC (Personal Computer), a tablet PC, a PDA (Personal Digital Assistant), a smart phone, and the like. The terminal device 130 is arranged in each clinical department within the medical facility. The terminal device 130 receives medical record information such as symptoms of the subject and doctor's findings by an operator. In addition, an operator inputs an examination order to the terminal device 130 . The terminal device 130 transmits the input examination order to the medical image diagnostic apparatus 110 or the server device 120 .

The biometric data measuring device 140 corresponds to a device that measures biometric data such as physical characteristics and behavioral patterns of a subject. Biological data includes, for example, electrocardiographic waveforms, pulse, blood flow, blood pressure, skin temperature, brain waves, eye movements, blood sugar levels, blood oxygen saturation, and the like. The biological data measuring device 140 measures biological data of the subject in real time and transmits the measured biological data to the medical image diagnostic device 110 and the server device 120 .

The biological data measurement device 140 may be a wearable device that can be worn by the subject at all times. Such wearable devices can acquire biometric data anywhere as long as they are worn by the subject.

The biometric data measuring device 140 may acquire biometric data from a non-contact device. Specifically, the non-contact device corresponds to a web camera, a thermography camera, a microphone, and the like placed indoors, and acquires biometric data by image analysis and sound analysis. Note that when biometric data is acquired using a non-contact device, the non-contact device may identify a subject using face recognition, voice recognition, or the like.

The biological data may be medical image data acquired by a medical image diagnostic device, an ultrasonic diagnostic device, or the like. Specifically, the biological data may be Doppler data obtained by an ultrasonic diagnostic apparatus or the like. Therefore, the biological data measuring device 140 does not have to be a single device as long as it can acquire biological data about the subject. That is, as the biological data measuring device 140, a medical image diagnostic device, an ultrasonic diagnostic device, or the like may be used.

In one embodiment, the biological data measuring device 140 corresponds to an electrocardiograph. An electrocardiograph acquires an electrocardiographic waveform of a subject. Types of electrocardiographs include stationary electrocardiographs installed in operating rooms and the like, and Holter electrocardiographs that can be worn by subjects at all times.

Next, the operation of the medical image diagnostic apparatus 110 configured as described above will be described with reference to the flowchart of FIG. 3 and the schematic diagram of FIG.

FIG. 3 is a flowchart illustrating operations in the first embodiment. In the following, as a specific example, it is assumed that a doctor performs an X-ray contrast examination on the coronary arteries of a subject suspected of having coronary spasm angina. An electrocardiograph is attached to the subject, and the medical image diagnostic apparatus 110 acquires biological data (electrocardiographic waveform) of the subject in real time. It is assumed that the medical image diagnostic apparatus 110 is an X-ray CT apparatus.

Coronary spasm angina is angina pectoris caused by spasm and abrupt constriction of a portion of a coronary artery. Coronary spasm angina can occur at dawn and even at rest during the night. Since attacks occur even at rest in this way, there are various causes of attacks due to coronary spasm angina.

FIG. 4 is a schematic diagram for explaining the operation in the first embodiment. The schematic diagram of FIG. 4 mainly shows the flow from step ST104 to step ST109 of the flowchart of FIG.

First, the medical image diagnostic apparatus 110 acquires subject information (patient information) regarding a subject to be examined from an examination reservation system or the like via the communication interface 116 . The patient information includes, for example, patient ID, patient name, date of birth, age, weight, sex, and examination site. Note that the subject information may include implant information indicating an implant that the subject has.

Note that the date and time when a subject performs an examination may be determined from a probability distribution calculated using at least one of the past biometric data of the subject and the past biometric data of another subject. In this probability distribution, for example, a time period such as "the event occurrence probability is 70% for 15 minutes from 2 hours later" is predicted. Therefore, the operator can proceed with preparations for the inspection with plenty of time to spare.

(Step ST101)
An imaging setup is performed in the medical imaging apparatus 110 . Specifically, in the imaging setup, the operator places the subject P on the tabletop, and inserts a tube for injecting a contrast agent into the subject's veins. Note that contrast setup may be performed after positioning imaging.

(Step ST102)
The processing circuit 115 sets an imaging plan including imaging conditions for positioning imaging according to the operation of the input interface 114 by the operator.

(Step ST103)
The processing circuit 115 acquires positioning image data of the subject P for determining the scan range, region of interest, imaging conditions, and the like. The positioning image data is acquired by acquiring projection data for the entire circumference of the subject P by helical scanning or non-helical scanning, for example. Specifically, the processing circuit 115 performs a helical scan or a non-helical scan over a wide area such as the entire chest including the heart of the subject P at a dose lower than that of the main scan.

The processing circuit 115 can reconstruct three-dimensional X-ray CT image data (volume data) from the projection data regarding the subject P by the image generation function 115b. Also, the processing circuit 115 generates a two-dimensional positioning image corresponding to an arbitrary direction based on the reconstructed volume data. Note that the positioning image may use the aforementioned volume data as three-dimensional positioning image data.

(Step ST104)
The processing circuit 115 acquires biological data of the subject P in real time by the acquisition function 115c. Specifically, the processing circuit 115 acquires electrocardiographic waveform (electrocardiogram) data as biological data via an electrocardiograph attached to the subject P. FIG.

(Step ST105)
The processing circuit 115 predicts the occurrence time zone of the event by the prediction function 115d. Specifically, the processing circuit 115 calculates the time at which the event is most likely to occur based on the biological data of the subject acquired in real time and the probability distribution regarding the event (attack of coronary spasm angina pectoris). _Predict t1.

(Step ST106)
The processing circuit 115 sets monitoring conditions for performing monitoring imaging of the subject P according to the operation of the input interface 114 by the operator. Monitoring conditions include imaging conditions and imaging conditions. Contrast conditions include, for example, the injection speed, injection amount, and injection time of the contrast medium. In addition, the processing circuit 115 sets a region of interest ROI for monitoring imaging on the positioning image by the operator's operation of the input interface 114 .

(Step ST107)
The processing circuit 115 controls imaging of the subject based on the occurrence time period by the imaging control function 115e. Specifically, the processing circuit 115 performs monitoring photography so that the _main scan can be performed at time t1. For example, processing circuitry 115 determines when to inject the contrast agent based _on the time t1 of the seizure. Then, the processing circuit 115 controls an injector that injects the contrast medium into the subject P based on the contrast conditions. Also, the processing circuit 115 controls the X-ray source and the X-ray detector to perform monitoring imaging based on the imaging conditions.

During monitoring imaging, the processing circuit 115 performs reconstruction processing on projection data output from the X-ray detector via a DAS (Data Acquisition System), and sequentially creates a plurality of medical image data (monitoring image data). and save it in the memory 112 .

(Step ST108)
The processing circuit 115 determines whether the index value of the density of the contrast agent in the pixels of the region of interest ROI of the medical image data (monitoring image acquired by monitoring imaging) has reached the threshold. This determination is performed, for example, by creating a Time Density Curve (TDC) representing the CT values (index values) of pixels in the region of interest ROI in time series, and comparing the CT values with a threshold. Note that this determination does not necessarily need to create a TDC, and can be performed by comparing the index value and the threshold value.

If the index value has not reached the threshold value, the process returns to step ST107, and the processing circuit 115 continues monitoring imaging. When the index value reaches the threshold value, the process proceeds to step ST109, and the processing circuit 115 terminates monitoring imaging.

(Step ST109)
The processing circuit 115 controls the X-ray source and the X-ray detector so that the main scan is executed at the timing when the monitoring imaging is completed. This main scan is, for example, a volume scan capable of imaging the entire heart in one rotation scan.

During the main scan, the processing circuit 115 performs reconstruction processing on the projection data output from the X-ray detector via the DAS, generates medical image data (tomographic image data and volume data), and stores the data in the memory 112. Save to Volume data is generated by interpolating a plurality of reconstructed tomogram data.

It should be noted that the above flowchart is only an example, and intermediate processing may be omitted or additional processing may be added as long as imaging control is performed using a probability distribution. Also, the imaging setup in step ST101 may include any preparations as long as they are preparations for imaging and preparations for the subject. For example, in an imaging setup, in addition to preparing a contrast medium, an ECG monitor may be attached to the subject, a respiratory sensor may be attached, and the like.

Further, in the examination of the coronary arteries, the X-ray angiographic examination using the X-ray CT apparatus has been described above, but the examination is not limited to this. For example, coronary artery MRA (Magnetic Resonance Angiography) may be performed using an MRI apparatus. In coronary MRA, the imaging set-up may include additions such as attachment of a local coil to the subject.

As described above, according to the first embodiment, the medical image diagnostic apparatus 110 acquires the biological data of the subject in real time, and based on the acquired biological data and the probability distribution of the event, the occurrence of an event related to the subject. The time period can be predicted, and imaging of the subject can be controlled based on the predicted time period of occurrence.

Further, according to the first embodiment, the medical image diagnostic apparatus 110 can acquire biological data of a subject placed on a medical imaging apparatus for imaging the subject in real time.

Further, according to the first embodiment, the medical image diagnostic apparatus 110 can acquire biological data in real time based on medical images captured by another medical imaging apparatus.

Further, according to the first embodiment, the medical image diagnostic apparatus 110 can acquire biological data in real time based on medical images captured by the ultrasonic diagnostic apparatus.

Further, according to the first embodiment, the medical image diagnostic apparatus 110 can calculate the probability distribution using at least one of the past biological data of the subject and the biological data of other subjects regarding the event.

Further, according to the first embodiment, the medical image diagnostic apparatus 110 can predict the occurrence time zone by updating the probability distribution using biological data.

Further, according to the first embodiment, the medical image diagnostic apparatus 110 can control the start or end of imaging based on the occurrence time period.

Further, according to the first embodiment, the medical image diagnostic apparatus 110 can control the start or end of administration of the contrast agent to the subject based on the occurrence time period.

Therefore, the medical image diagnostic apparatus 110 can perform an examination in accordance with the occurrence time of the event, so that the examination of the subject can be performed at the optimum timing.

(Second embodiment)
In the first embodiment, the medical image diagnostic apparatus 110 predicts an event and controls imaging. On the other hand, in the second embodiment, a case will be described in which an event is predicted by a modality control device different from the medical image diagnostic device, and the modality control device instructs the medical image diagnostic device to control imaging.

FIG. 5 is a block diagram showing a configuration example of a medical information processing system according to the second embodiment. For example, as shown in FIG. 5, the medical information processing system 100 according to the present embodiment includes a medical image diagnostic device 110, a server device 120, a terminal device 130, a biological data measuring device 140, and a modality control device 200. Prepare.

FIG. 6 is a block diagram showing a configuration example of the modality control device of FIG. For example, as shown in FIG. 6, the modality control device 200 according to this embodiment includes a memory 210, a display 220, an input interface 230, a processing circuit 240, and a communication interface 250.

Display 220, input interface 230, and communication interface 250 have substantially the same configurations and functions as display 113, input interface 114, and communication interface 116 in FIG.

The modality control device 200 is a device that controls the medical image diagnostic device 110, interprets medical images, and the like. Specifically, the modality control device 200 controls the medical image diagnostic device 110 regarding imaging. The modality control device 200 may also receive medical image data such as positioning images captured by the medical image diagnostic device 110 and display the received medical image data on the display 220 .

Memory 210 has substantially the same configuration as memory 112 in FIG. The memory 210 stores, for example, raw data and medical image data acquired by the medical image diagnostic apparatus 110 . The memory 210 also stores control programs and data according to the present embodiment. Note that the storage area of the memory 210 may be in an external storage device connected to the hospital LAN 150 .

The processing circuit 240 has, as hardware resources, a processor (not shown), ROM (Read-Only Memory), RAM and other memory, and controls the modality control device 200 . The processing circuitry 240 has an acquisition function 240a, a prediction function 240b and a control directing function 240c. Various functions performed by the acquisition function 240a, the prediction function 240b, and the control instruction function 240c are stored in the memory in the form of computer-executable programs. The processing circuit 240 is a processor that implements functions corresponding to each program by reading programs corresponding to these various functions from the memory and executing the programs. In other words, the processing circuit 240 in a state where each program has been read has a plurality of functions shown in the processing circuit 240 of FIG.

The processor in the processing circuit 240 implements various functions by reading and executing programs stored in the memory 210 . Note that instead of storing the program in the memory 210, the program may be configured to be directly embedded in the circuit of the processor. In this case, the processor implements its functions by reading and executing the program embedded in the circuit. Acquisition function 240a, prediction function 240b, and control instruction function 240c of processing circuit 240 are examples of an acquisition unit, a prediction unit, and an instruction unit, respectively.

Since the acquisition function 240a and the prediction function 240b are substantially the same functions as the acquisition function 115c and the prediction function 115d of FIG. 2, description thereof will be omitted.

The control instruction function 240c is a function for instructing the modality device to control imaging of the subject based on the occurrence time period. Specifically, the processing circuit 240 uses the control instruction function 240c to instruct the medical image diagnostic apparatus 110 to control the start or end of imaging in the medical image diagnostic apparatus 110 based on the occurrence time period. The processing circuitry 240 may also instruct the medical image diagnostic apparatus 110 to control the start or end of administration of the contrast agent to the subject based on the occurrence time period.

FIG. 7 is a flowchart illustrating operations in the second embodiment. The specific example of FIG. 7 is substantially the same as the specific example according to the first embodiment.

First, the modality control device 200 acquires patient information regarding a subject to be examined from an examination reservation system or the like via the communication interface 250 . Then, in the medical image diagnostic apparatus 110, the processing circuit 240 starts processing after preparation for the examination of the subject P is completed.

(Step ST201)
The processing circuit 240 acquires biological data of the subject P in real time by the acquisition function 240a. Specifically, the processing circuit 240 acquires electrocardiographic waveform (electrocardiogram) data as biological data via an electrocardiograph attached to the subject P. FIG.

(Step ST202)
The processing circuitry 240 predicts the event occurrence time zone using the prediction function 240b. Specifically, the processing circuit 240 calculates the time at which the event is most likely to occur based on real-time biological data of the subject and the probability distribution of the event (attack of coronary spasm angina). _Predict t1.

(Step ST203)
The processing circuit 240 instructs the modality apparatus to control imaging of the subject based on the occurrence time period by the control instruction function 240c. Specifically, the processing circuit 240 instructs the medical image diagnostic apparatus 110 to control the operation related to imaging at the timing based _on the predicted time t1.

As described above, according to the second embodiment, the modality control device 200 acquires the biological data of the subject in real time, and based on the acquired biological data and the probability distribution of the event, the occurrence of an event related to the subject. It is possible to predict the time period and instruct the modality device to control imaging of the subject based on the predicted time period of occurrence.

Therefore, since the modality control apparatus 200 can issue control instructions to the modality apparatus in accordance with the event occurrence time zone, it is possible to perform an examination on the subject at an appropriate timing.

(Third embodiment)
In the first and second embodiments, a case has been described in which biometric data is acquired from a subject or patient in an operating room or medical facility, and imaging by a medical image diagnostic apparatus is controlled. On the other hand, in the third embodiment, a medical information management apparatus acquires biometric data from a patient outside a medical facility, predicts an event from the acquired biodata, and generates and transmits examination reservation information. do.

FIG. 8 is a block diagram illustrating a network configuration including the medical information processing system 100 according to the third embodiment. For example, as shown in FIG. 8, the medical information processing system 100 according to this embodiment includes a medical image diagnostic apparatus 110, a server apparatus 120, a terminal apparatus 130, and a medical information management apparatus 300. In the network configuration according to the third embodiment, the biological data measuring device 140 is not included in the medical information processing system 100, but can transmit various data to the medical information management device 300 or the like via the Internet and a firewall. be. The biological data measuring device 140 may be included in the medical information processing system 100 connected to the hospital LAN 150 .

9 is a block diagram showing a configuration example of the medical information management apparatus of FIG. 8. FIG. For example, as shown in FIG. 9, a medical information management apparatus 300 according to this embodiment includes a memory 310, a display 320, an input interface 330, a processing circuit 340, and a communication interface 350.

Display 320, input interface 330, and communication interface 350 have substantially the same configurations and functions as display 113, input interface 114, and communication interface 116 in FIG.

The medical information management apparatus 300 is an apparatus that generates and transmits appointment information for examinations performed using the medical image diagnostic apparatus 110 . The medical information management apparatus 300 generates, for example, an examination order as reservation information and transmits it to the server apparatus 120 or registers it in the RIS.

Memory 310 has substantially the same configuration as memory 112 in FIG. Memory 310 stores, for example, reservation information generated by processing circuitry 340 . The memory 310 also stores control programs and data according to the present embodiment. Note that the storage area of the memory 310 may be in an external storage device connected to the hospital LAN 150 .

The processing circuit 340 has, as hardware resources, a processor (not shown), a memory such as a ROM (Read-Only Memory) and a RAM, and controls the medical information management apparatus 300 . The processing circuit 340 has an acquisition function 340a, a prediction function 340b, a generation function 340c and a transmission function 340d. Various functions performed by the acquisition function 340a, the prediction function 340b, the generation function 340c, and the transmission function 340d are stored in the memory in the form of programs executable by a computer. The processing circuit 340 is a processor that reads programs corresponding to these various functions from the memory and executes them, thereby implementing functions corresponding to each program. In other words, the processing circuit 340 in a state where each program has been read has a plurality of functions shown in the processing circuit 340 of FIG.

The processor in the processing circuit 340 implements various functions by reading and executing programs stored in the memory 310 . Note that instead of storing the program in the memory 310, the program may be configured to be directly embedded in the circuit of the processor. In this case, the processor implements its functions by reading and executing the program embedded in the circuit. Acquisition function 340a, prediction function 340b, generation function 340c, and transmission function 340d of processing circuit 340 are examples of an acquisition unit, a prediction unit, a generation unit, and a transmission unit, respectively.

Hereinafter, the acquisition function 340a and the prediction function 340b are substantially the same functions as the acquisition function 115c and the prediction function 115d of FIG. 2, and therefore description thereof is omitted.

The generation function 340c is a function for generating examination appointment information regarding a subject based on an occurrence time period. Specifically, the processing circuit 340 uses the generation function 340c to generate an inspection order for the subject based on the generation time period.

The transmission function 340d is a function for transmitting reservation information to a device managed by a medical facility that conducts an examination. Specifically, the processing circuit 340 uses the transmission function 340d to transmit the generated inspection order to the server device 120 or the like in which the HIS is installed. In addition, the processing circuit 340 may notify the subject of the information about the date and time of the examination using e-mail or the like.

FIG. 10 is a flowchart illustrating operations in the third embodiment. In the following, as a specific example, it is assumed that the occurrence of an event is predicted from biometric data of an out-of-hospital patient, and that reservation information is generated and transmitted. A Holter electrocardiograph is attached to this patient, and the medical information management apparatus 300 acquires biological data (electrocardiographic waveform) of the subject in real time.

(Step ST301)
The processing circuit 340 acquires biological data of the subject P in real time by the acquisition function 340a. Specifically, the processing circuit 340 acquires electrocardiographic waveform (electrocardiogram) data as biological data via a Holter electrocardiograph attached to the subject P. FIG.

(Step ST302)
The processing circuitry 340 predicts the event occurrence time zone using the prediction function 340b. Specifically, the processing circuit 340 predicts the date and time when an event will occur based on the biological data of the subject acquired in real time and the probability distribution of events (for example, seizures that occur irregularly).

(Step ST303)
The processing circuitry 340 uses the generation function 340c to generate examination appointment information for the subject based on the occurrence time period. Specifically, the processing circuit 340 generates an inspection order for performing an inspection on the date and time when the event occurs.

(Step ST304)
The processing circuit 340 uses the transmission function 340d to transmit the generated reservation information to the device managed by the medical facility that conducts the examination. Specifically, the processing circuit 340 transmits the inspection order to the server device 120 or the like in which the HIS is installed. In addition, the processing circuit 340 notifies the subject of information regarding the examination date and time by e-mail.

As described above, according to the third embodiment, the medical information management apparatus 300 obtains the biological data of the subject in real time, and based on the obtained biological data and the probability distribution regarding the event, determines the event regarding the subject. Predicting the occurrence time zone, generating test reservation information for the subject based on the predicted occurrence time zone, and transmitting the generated reservation information to the device managed by the medical facility that conducts the test. can be done.

Therefore, the medical information management apparatus 300 can make an examination reservation in accordance with the event occurrence time zone, so that the examination of the subject can be performed at an appropriate timing.

(Modification)
In the third embodiment, the destination of the reservation information is basically the medical facility where the patient visits. On the other hand, in a variant, the destination of the appointment information may be a medical facility based on the patient's location information.

Specifically, the medical information management apparatus 300 acquires the patient's position information together with the biometric data. If the event occurrence time period is approaching several hours later, the medical information management apparatus 300 may notify the patient of information on medical facilities where information inspection is possible based on the position information. For example, when the patient instructs a medical facility, the medical information management apparatus 300 transmits the reservation information to the apparatus managed by the instructed medical facility.

Therefore, the medical information management apparatus 300 can make an examination reservation in consideration of the patient's position information.

According to at least one of the embodiments described above, it is possible to perform an examination on a subject at optimum timing.

While several embodiments of the invention have been described, these embodiments have been presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and modifications can be made without departing from the scope of the invention. These embodiments and their modifications are included in the scope and spirit of the invention, as well as the scope of the invention described in the claims and equivalents thereof.

100 medical information processing system 150 hospital LAN
P Subject

Claims (8)

an acquisition unit that acquires biological data of a subject in real time;
a prediction unit that predicts an occurrence time zone of the event related to the subject based on the biometric data and the probability distribution related to the event;
A medical image diagnostic apparatus, comprising: a control unit that controls start or end of administration of a contrast agent to the subject based on the occurrence time period. further comprising a medical imaging device for imaging the subject;
2. The medical image diagnostic apparatus according to claim 1, wherein said acquisition unit acquires biological data of said subject placed on said medical imaging apparatus in real time. 3. The medical image diagnostic apparatus according to claim 2, wherein said acquisition unit acquires in real time said biological data based on a medical image captured by another medical imaging apparatus different from said medical imaging apparatus. 3. The medical image diagnostic apparatus according to claim 2, wherein said acquisition unit acquires said biological data based on a medical image captured by an ultrasonic diagnostic apparatus in real time. 5. Any one of claims 1 to 4, wherein the prediction unit calculates the probability distribution using at least one of past biometric data of the subject and biometric data of another subject regarding the event. 2. The medical image diagnostic apparatus according to 1. The medical image diagnostic apparatus according to any one of claims 1 to 5, wherein the prediction unit predicts the occurrence time zone by updating the probability distribution using the biometric data. The medical image diagnostic apparatus according to any one of claims 1 to 6, wherein the control unit controls start or end of imaging of the subject based on the occurrence time period. an acquisition unit that acquires biological data of a subject in real time;
a prediction unit that predicts an occurrence time zone of the event related to the subject based on the biometric data and the probability distribution related to the event;
and an instruction unit that instructs a modality apparatus to start or end administration of a contrast agent to the subject based on the occurrence time period.

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